476 research outputs found
Investment and Pricing with Spectrum Uncertainty: A Cognitive Operator's Perspective
This paper studies the optimal investment and pricing decisions of a
cognitive mobile virtual network operator (C-MVNO) under spectrum supply
uncertainty. Compared with a traditional MVNO who often leases spectrum via
long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by
both sensing the empty "spectrum holes" of licensed bands and dynamically
leasing from the spectrum owner. As a result, a C-MVNO can make flexible
investment and pricing decisions to match the current demands of the secondary
unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is
typically cheaper, but the obtained useful spectrum amount is random due to
primary licensed users' stochastic traffic. The C-MVNO needs to determine the
optimal amounts of spectrum sensing and leasing by evaluating the trade off
between cost and uncertainty. The C-MVNO also needs to determine the optimal
price to sell the spectrum to the secondary unlicensed users, taking into
account wireless heterogeneity of users such as different maximum transmission
power levels and channel gains. We model and analyze the interactions between
the C-MVNO and secondary unlicensed users as a Stackelberg game. We show
several interesting properties of the network equilibrium, including threshold
structures of the optimal investment and pricing decisions, the independence of
the optimal price on users' wireless characteristics, and guaranteed fair and
predictable QoS among users. We prove that these properties hold for general
SNR regime and general continuous distributions of sensing uncertainty. We show
that spectrum sensing can significantly improve the C-MVNO's expected profit
and users' payoffs.Comment: A shorter version appears in IEEE INFOCOM 2010. This version has been
submitted to IEEE Transactions on Mobile Computin
Optimal Pricing Effect on Equilibrium Behaviors of Delay-Sensitive Users in Cognitive Radio Networks
This paper studies price-based spectrum access control in cognitive radio
networks, which characterizes network operators' service provisions to
delay-sensitive secondary users (SUs) via pricing strategies. Based on the two
paradigms of shared-use and exclusive-use dynamic spectrum access (DSA), we
examine three network scenarios corresponding to three types of secondary
markets. In the first monopoly market with one operator using opportunistic
shared-use DSA, we study the operator's pricing effect on the equilibrium
behaviors of self-optimizing SUs in a queueing system. %This queue represents
the congestion of the multiple SUs sharing the operator's single \ON-\OFF
channel that models the primary users (PUs) traffic. We provide a queueing
delay analysis with the general distributions of the SU service time and PU
traffic using the renewal theory. In terms of SUs, we show that there exists a
unique Nash equilibrium in a non-cooperative game where SUs are players
employing individual optimal strategies. We also provide a sufficient condition
and iterative algorithms for equilibrium convergence. In terms of operators,
two pricing mechanisms are proposed with different goals: revenue maximization
and social welfare maximization. In the second monopoly market, an operator
exploiting exclusive-use DSA has many channels that will be allocated
separately to each entering SU. We also analyze the pricing effect on the
equilibrium behaviors of the SUs and the revenue-optimal and socially-optimal
pricing strategies of the operator in this market. In the third duopoly market,
we study a price competition between two operators employing shared-use and
exclusive-use DSA, respectively, as a two-stage Stackelberg game. Using a
backward induction method, we show that there exists a unique equilibrium for
this game and investigate the equilibrium convergence.Comment: 30 pages, one column, double spac
Cloud/fog computing resource management and pricing for blockchain networks
The mining process in blockchain requires solving a proof-of-work puzzle,
which is resource expensive to implement in mobile devices due to the high
computing power and energy needed. In this paper, we, for the first time,
consider edge computing as an enabler for mobile blockchain. In particular, we
study edge computing resource management and pricing to support mobile
blockchain applications in which the mining process of miners can be offloaded
to an edge computing service provider. We formulate a two-stage Stackelberg
game to jointly maximize the profit of the edge computing service provider and
the individual utilities of the miners. In the first stage, the service
provider sets the price of edge computing nodes. In the second stage, the
miners decide on the service demand to purchase based on the observed prices.
We apply the backward induction to analyze the sub-game perfect equilibrium in
each stage for both uniform and discriminatory pricing schemes. For the uniform
pricing where the same price is applied to all miners, the existence and
uniqueness of Stackelberg equilibrium are validated by identifying the best
response strategies of the miners. For the discriminatory pricing where the
different prices are applied to different miners, the Stackelberg equilibrium
is proved to exist and be unique by capitalizing on the Variational Inequality
theory. Further, the real experimental results are employed to justify our
proposed model.Comment: 16 pages, double-column version, accepted by IEEE Internet of Things
Journa
Multilevel Pricing Schemes in a Deregulated Wireless Network Market
Typically the cost of a product, a good or a service has many components.
Those components come from different complex steps in the supply chain of the
product from sourcing to distribution. This economic point of view also takes
place in the determination of goods and services in wireless networks. Indeed,
before transmitting customer data, a network operator has to lease some
frequency range from a spectrum owner and also has to establish agreements with
electricity suppliers. The goal of this paper is to compare two pricing
schemes, namely a power-based and a flat rate, and give a possible explanation
why flat rate pricing schemes are more common than power based pricing ones in
a deregulated wireless market. We suggest a hierarchical game-theoretical model
of a three level supply chain: the end users, the service provider and the
spectrum owner. The end users intend to transmit data on a wireless network.
The amount of traffic sent by the end users depends on the available frequency
bandwidth as well as the price they have to pay for their transmission. A
natural question arises for the service provider: how to design an efficient
pricing scheme in order to maximize his profit. Moreover he has to take into
account the lease charge he has to pay to the spectrum owner and how many
frequency bandwidth to rent. The spectrum owner itself also looks for
maximizing its profit and has to determine the lease price to the service
provider. The equilibrium at each level of our supply chain model are
established and several properties are investigated. In particular, in the case
of a power-based pricing scheme, the service provider and the spectrum owner
tend to share the gross provider profit. Whereas, considering the flat rate
pricing scheme, if the end users are going to exploit the network intensively,
then the tariffs of the suppliers (spectrum owner and service provider)
explode.Comment: This is the last draft version of the paper. Revised version of the
paper accepted by ValueTools 2013 can be found in Proceedings of the 7th
International Conference on Performance Evaluation Methodologies and Tools
(ValueTools '13), December 10-12, 2013, Turin, Ital
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